• DocumentCode
    2069176
  • Title

    Efficient Recommender Systems

  • Author

    Bergemann, D. ; Ozmen, Deran

  • Author_Institution
    Yale Univ., New Haven, CT
  • fYear
    2006
  • fDate
    26-29 June 2006
  • Firstpage
    41
  • Lastpage
    41
  • Abstract
    We study the efficient allocation of buyers in the presence of recommender systems. A recommender system affects the market in two ways: (i) it creates value by reducing product uncertainty for the customers and hence (ii) its recommendations can be offered as add-ons, which generates informational externalities. We investigate the impact of these factors on the efficient allocation of buyers across different products. We find that the efficient allocation requires that the seller with the recommender system has full market share. If the recommender system is sufficiently effective in reducing uncertainty, it is optimal to have some products to be purchased by a larger group of people than others. The large group consists of customers with flexible tastes
  • Keywords
    information filters; resource allocation; retail data processing; buyer allocation; product uncertainty; recommender systems; Recommender systems;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    E-Commerce Technology, 2006. The 8th IEEE International Conference on and Enterprise Computing, E-Commerce, and E-Services, The 3rd IEEE International Conference on
  • Conference_Location
    San Francisco, CA
  • Print_ISBN
    0-7695-2511-3
  • Type

    conf

  • DOI
    10.1109/CEC-EEE.2006.42
  • Filename
    1640296